针对传统永磁同步电机(PMSM)PWM电流预测控制中电机参数扰动造成的电流静差及振荡问题,提出基于龙伯格(Luenberger)观测器的PWM电流预测控制。首先,将系统参数扰动引入到电机电压方程,构建在参数扰动中拥有优良性能的Luenberger观测器来观测系统扰动。其次,离散化Luenberger扰动观测器,通过极点配置分析系统稳定性。最后,将观测器估计系统扰动引入含参数扰动项的电压方程中,为PWM电流预测控制算法提供实时性扰动补偿。仿真结果表明,所提算法能够快速无静差地观测出系统扰动,有效避免参数扰动造成的电流静差及振荡问题,提高电流预测算法的鲁棒性。

Since motor parameter disturbance could cause current static error and oscillation in PWM predictive current control of permanent magnet synchronous motor (PMSM), PWM predictive current control based on Luenberger observer was proposed. Firstly, system parameter disturbance was introduced into the motor voltage equation, and Luenberger observer with excellent performance in parameter perturbation was constructed to observe the system disturbance. Then, Luenberger disturbance observer was discretized, and system stability was analyzed by pole assignment. Finally, disturbance from the observer was introduced into the voltage equation with parameter disturbance to provide realtime disturbance compensation for the algorithm. Simulation results showed that the proposed algorithm could rapidly observe the disturbance of the system without static error, effectively avoid the current static error and oscillation caused by inductance parameter error, and improved the robustness of current prediction algorithm.

TM 301.2

国家自然科学基金项目(61503161);江苏省自然科学基金面上项目(BK20161229);江苏省产学研前瞻性联合研究项目(BY2016073-01)